1. Field of the Invention
The present invention relates to an eye image recognition method for extracting a region of a pupil of an eye from a captured image including the eye, and further relates to eye image selection method and system for selecting an image including eye data about a pupil and its peripheral portion of an eye from among consecutively captured images each including the eye. The eye data is used for individual identification of an animal, such as a human being, a horse or a cow.
2. Description of the Related Art
A technique is disclosed, for example, in JP-A-4-264985, for carrying out individual identification based on a human face. In the disclosed technique, regions of the eyes, nose and so on are individually extracted from an input image of the whole face, captured by a camera, so as to be subjected to identification processes, respectively. For locating, for example, the eye region to be extracted, a rectangular region is preset in the input face image and projected in vertical and horizontal directions, and positions having the minimum luminance value in the projected regions are considered to define the center of the eye.
In the foregoing technique, it is necessary that the human face is adequately positioned relative to the camera so that the eyes and so forth can be present in the corresponding preset rectangular regions.
However, in practice, human faces are not always positioned adequately relative to cameras, and further, it is almost impossible to adequately position faces of other animals relative to cameras. Thus, for automatically searching out the position of an eye for extraction, it is necessary to select an image, which includes the eye in a preset region, from a number of consecutively captured images.
In view of this, a technique has been demanded which can achieve automatic selection of such an image from the consecutively captured images.
On the other hand, when carrying out individual identification using eye data of a human being or an animal of another kind, it is necessary to use an enlarged image of an eye for obtaining as many eye data as possible. However, in the enlarged eye image, those portions, such as an eyebrow, eyelashes, a mole and a shadow, may appear as regions having the same or like density (luminance) values as a pupil of the eye. Therefore, it is difficult to identify a region of the pupil only based on density data, such as differences in density.
Specifically, as shown in FIG. 2, an eyebrow, eyelashes and a mole exist in an image of an eye as regions having the same or like density values as the pupil of the eye. Accordingly, when the image is simply projected in vertical and horizontal directions, a plurality of minimum value regions are located so that it is difficult to extract only the region of the pupil with accuracy.
In view of this, a technique has been demanded which can extract the pupil region with accuracy even if the input image includes portions having the same or like density values as the pupil region.